About the role
Who we are Odyssey is an AI lab pioneering general-purpose world models: causal, multimodal systems that learn to predict and interact with the world over long horizons, while generating real-time, interactive simulations from any starting point. This foundational technology promises to revolutionize robotics, science, healthcare, education, gaming, defense, and beyond. What we’re looking for We need a senior data operations leader who can own the entire data lever for Odyssey's world models. This person deeply understands what multimodal data looks like across gaming and robotics, knows the difference between fine-tuning expert networks and acquiring video, audio, and egocentric datasets, and has the technical depth to have contributed to research themselves. You'll shape our data strategy, close partnerships, manage a multi-million dollar budget, and build an organisation that could scale to hundreds of people. This is a strategic, highly autonomous role in a company where everyone - including ops - is deeply technical. What you’ll do Define data acquisition strategy across multimodal sources - video, audio, egocentric capture, simulation, robotic sensor data. Decide what we need next, where it comes from, and how we get it. Build a diversified pipeline of vendors, publishers, robotics partners, expert networks, and custom-collected data, prioritised by impact on model quality and cost. Close and manage data partnerships. Identify, evaluate, and negotiate deals. Build systems that manage relationships once they're live - tracking expirations, exclusivity, and renewals. Own data mix and composition. Work with research and product to define the right blend of sources, domains, modalities, and quality tiers for each training run or product feature. Translate model needs into concrete acquisition plans. Identify gaps before they hurt us. Design systems with research and engineering that surface what's missing - through evals, error analysis, coverage maps, and tight feedback loops. Turn gaps into plans quickly. Build and scale the data organisation. Lead a small team today. Define operating cadence, metrics, and the bar. Over time, determine the right mix of in-house teams, contractors, and vendor partnerships to scale the function. Own the data ops budget. Manage a data budget in the tens of millions allocated to data acquisition and processing. Make trade-offs across sources, quality, and speed. Build reporting that lets leadership see what we're spending and what we're getting for it.
